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Use random_itensor and random_mps #311

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Use random_itensor and random_mps #311

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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
ChainRulesCore = "1.10"
DataFrames = "1.6"
HDF5 = "0.13.1, 0.14, 0.15, 0.16"
ITensors = "0.3.20"
ITensors = "0.6.8"
JLD2 = "0.4.14"
Observers = "0.2"
Optimisers = "0.2"
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -181,7 +181,7 @@ H = MPO(os, hilbert)
nsweeps = 10
maxdim = [10, 20, 30, 50, 100]
cutoff = 1e-10
Edmrg, Φ = dmrg(H, randomMPS(hilbert); outputlevel=0, nsweeps, maxdim, cutoff);
Edmrg, Φ = dmrg(H, random_mps(hilbert); outputlevel=0, nsweeps, maxdim, cutoff);
@printf("\nGround state energy from DMRG: %.10f\n\n", Edmrg)

# layer of single-qubit Ry gates
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2 changes: 1 addition & 1 deletion examples/05_finitetemperature.jl
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Expand Up @@ -87,7 +87,7 @@ H = MPO(ampo, sites)
# Density-matrix renormalization group
dmrg_iter = 5 # DMRG steps
dmrg_cutoff = 1E-10 # Cutoff
Ψ0 = randomMPS(sites) # Initial state
Ψ0 = random_mps(sites) # Initial state
sweeps = Sweeps(dmrg_iter)
maxdim!(sweeps, 10, 20, 30, 40, 50, 100)
cutoff!(sweeps, dmrg_cutoff)
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2 changes: 1 addition & 1 deletion examples/09_qst_ising.jl
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Expand Up @@ -25,7 +25,7 @@ H = MPO(ampo, sites)
# Run DMRG
dmrg_iter = 5 # DMRG steps
dmrg_cutoff = 1E-10 # Cutoff
Ψ0 = randomMPS(sites) # Initial state
Ψ0 = random_mps(sites) # Initial state
sweeps = Sweeps(dmrg_iter)
maxdim!(sweeps, 10, 20, 30, 40, 50, 100)
cutoff!(sweeps, dmrg_cutoff)
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2 changes: 1 addition & 1 deletion examples/10_vqe.jl
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Expand Up @@ -33,7 +33,7 @@ H = MPO(os, hilbert)
nsweeps = 10
maxdim = [10, 20, 30, 50, 100]
cutoff = 1e-10
Edmrg, Φ = dmrg(H, randomMPS(hilbert); outputlevel=0, nsweeps, maxdim, cutoff);
Edmrg, Φ = dmrg(H, random_mps(hilbert); outputlevel=0, nsweeps, maxdim, cutoff);
@printf("\nGround state energy from DMRG: %.10f\n\n", Edmrg)

# layer of single-qubit Ry gates
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4 changes: 2 additions & 2 deletions src/randomstates.jl
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Expand Up @@ -281,7 +281,7 @@ function randomstate(ElT::Type{<:Number}, T::Type, sites::Vector{<:Index}; kwarg
if T == MPS
# Build MPS by random parameter initialization
alg == "rand" && (M = random_mps(ElT, sites, χ, σ))
alg == "circuit" && (M = randomMPS(ElT, sites; linkdims=χ))
alg == "circuit" && (M = random_mps(ElT, sites; linkdims=χ))
elseif T == MPO
error("initialization of random MPO density matrix not yet implemented.")
elseif T == LPDO
Expand Down Expand Up @@ -358,7 +358,7 @@ function randomprocess(ElT::Type{<:Number}, T::Type, sites::Vector{<:Index}; kwa
if alg == "rand"
M = random_mpo(ElT, sites, χ, σ; processtags=processtags)
else
error("randomMPO with circuit initialization not implemented yet")
error("random_mpo with circuit initialization not implemented yet")
end
elseif T == LPDO
M = random_choi(ElT, sites, χ, ξ, σ; purifier_tags=purifier_tags)
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2 changes: 1 addition & 1 deletion test/chainrulestestutils.jl
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Expand Up @@ -32,7 +32,7 @@ end

function ChainRulesTestUtils.rand_tangent(rng::AbstractRNG, A::ITensor)
# TODO: generalize to sparse tensors
return isempty(inds(A)) ? ITensor(randn(eltype(A))) : randomITensor(eltype(A), inds(A))
return isempty(inds(A)) ? ITensor(randn(eltype(A))) : random_itensor(eltype(A), inds(A))
end

function ChainRulesTestUtils.rand_tangent(rng::AbstractRNG, x::Index)
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